scholarly journals Editorial: Neuro-motor control and feed-forward models of locomotion in humans

2015 ◽  
Vol 9 ◽  
Author(s):  
Marco Iosa ◽  
Leonardo Gizzi ◽  
Federica Tamburella ◽  
Nadia Dominici
Keyword(s):  
Motor Control ◽  
Forward Models ◽  
Feed Forward

Multilayer Feed Forward Models in Groundwater Level Forecasting Using Meteorological Data in Public Management

2018 ◽  
Vol 32 (15) ◽  
pp. 5041-5052 ◽  
Author(s):  
Georgios N. Kouziokas ◽  
Alexander Chatzigeorgiou ◽  
Konstantinos Perakis
Keyword(s):  
Groundwater Level ◽  
Public Management ◽  
Meteorological Data ◽  
Forward Models ◽  
Feed Forward

scholarly journals Spatial constancy mechanisms in motor control

2011 ◽  
Vol 366 (1564) ◽  
pp. 476-491 ◽  
Author(s):  
W. Pieter Medendorp
Keyword(s):  
Motor Control ◽  
Eye Movements ◽  
Three Dimensional ◽  
Spatial Updating ◽  
Feedback Processing ◽  
Feed Forward ◽  
Motor Information ◽  
Induced Motion ◽  
Forward Process ◽  
The Brain

The success of the human species in interacting with the environment depends on the ability to maintain spatial stability despite the continuous changes in sensory and motor inputs owing to movements of eyes, head and body. In this paper, I will review recent advances in the understanding of how the brain deals with the dynamic flow of sensory and motor information in order to maintain spatial constancy of movement goals. The first part summarizes studies in the saccadic system, showing that spatial constancy is governed by a dynamic feed-forward process, by gaze-centred remapping of target representations in anticipation of and across eye movements. The subsequent sections relate to other oculomotor behaviour, such as eye–head gaze shifts, smooth pursuit and vergence eye movements, and their implications for feed-forward mechanisms for spatial constancy. Work that studied the geometric complexities in spatial constancy and saccadic guidance across head and body movements, distinguishing between self-generated and passively induced motion, indicates that both feed-forward and sensory feedback processing play a role in spatial updating of movement goals. The paper ends with a discussion of the behavioural mechanisms of spatial constancy for arm motor control and their physiological implications for the brain. Taken together, the emerging picture is that the brain computes an evolving representation of three-dimensional action space, whose internal metric is updated in a nonlinear way, by optimally integrating noisy and ambiguous afferent and efferent signals.

Automated Feed-Forward Learning for Pressure-Compensated Mobile Hydraulic Valves With Significant Dead-Zone

2017 ◽  
Author(s):  
Jarmo Nurmi ◽  
Jouni Mattila
Keyword(s):  
Motion Control ◽  
Dead Zone ◽  
Heavy Duty ◽  
Automated Identification ◽  
Forward Models ◽  
Feed Forward ◽  
Loop Control ◽  
Hydraulic Manipulators ◽  
Hydraulic Manipulator ◽  
Hydraulic Valves

Hydraulic manipulators on mobile machines, whose hydraulic actuators are usually controlled by mobile hydraulic valves, are being considered for robotic closed-loop control. A feed-forward-based strategy combining position and velocity feedback has been found to be an effective method for the motion control of pressure-compensated mobile hydraulic valves that have a significant dead zone. The feed-forward can be manually identified. However, manually identifying the feed-forward models for each valve-actuator pair is often very time-consuming and error-prone. For this practical reason, we propose an automated feed-forward learning method based on velocity and position feedback. We present experimental results for a heavy-duty hydraulic manipulator on a forest forwarder to demonstrate the effectiveness of the proposed method. These results motivate the automated identification of velocity feed-forward models for motion control of heavy-duty hydraulic manipulators controlled by pressure-compensated mobile hydraulic valves that have a significant input dead zone.

How do forward models work? And why would you want them?

2013 ◽  
Vol 36 (4) ◽  
pp. 349-350 ◽  
Author(s):  
Jeffrey Bowers
Keyword(s):  
Motor Control ◽  
Forward Models ◽  
Alternative Idea

AbstractThe project of coordinating perception, comprehension, and motor control is an exciting one, but I found it hard to follow some of Pickering & Garrod's (P&G's) arguments as presented. Consequently, my comment is not so much a disagreement with P&G but a query about the logic of forward models: It is not clear how they are supposed to work, nor why they are needed in this (or many other) contexts, and toward that end I present an alternative idea.

scholarly journals Twelve-picture RSVP sequences support feed-forward models of detection at 75 Hz

2013 ◽  
Vol 13 (9) ◽  
pp. 1047-1047
Author(s):  
M. C. Potter ◽  
C. E. Hagmann ◽  
B. Wyble
Keyword(s):  
Forward Models ◽  
Feed Forward

scholarly journals Tapping Behavior and Inter-Stimulus Interval in Isochronous Sound Sequence

2020 ◽  
Vol 9 (4) ◽  
pp. 1411-1415
Keyword(s):  
Motor Control ◽  
Control Mechanism ◽  
Top Down ◽  
Stimulus Interval ◽  
Feed Forward ◽  
Inter Stimulus Interval ◽  
Sensory Motor ◽  
Sound Sequence ◽  
Healthy Participants

The main objective of this study is to examine anticipatory tapping and reactive tapping under two different inter-stimulus interval (ISI). Healthy participants (N = 30) aged from 18 to 35 years voluntarily participated in the study. The results show that the ISI plays an important role in sensory motor synchronization (SMS). The analysis of asynchrony revealed that two different type of tapping occurred under two different ISI. Under short ISI (1000 ms), participants executed their responses before the tone (i.e., anticipatory tapping driven by feed-forward motor control). Under long ISI (2000 ms), participants executed their responses after the tone (i.e., reactive tapping driven by feed-back motor control mechanism). In summary, participants showed anticipatory tapping in the absence of top-down attention and reactive tapping with the involvement of top-down attention.

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